Influence of mixers on dry dispersion of nanoparticles in the cementitious composites

Main Article Content

Article Sidebar

Published Sep 14, 2021
Ujwal Shreenag Meda Bhavana B Radhakrishna

Abstract

Nanomaterials are gaining prominence in industries such as construction and medicine. Several parameters like durability and early strength development can be enhanced through the incorporation of nanomaterials into cementitious composites. The major challenge is to achieve uniform dispersion of nanomaterials within the composite’s matrix. Research on the dry dispersion of nanomaterials is in the nascent stage and hence a comparison does not exist between colloidal/wet dispersion and dry dispersion of nanomaterials. Often it is quite difficult to carry out dispersion experiments as it involves different types of expensive mixers and nanomaterials. Also, under experimental conditions, it is very difficult to assess the behavior of the particles during the dispersion process and is considered a research gap. Recently the use of high-performance computing to simulate the mixing of cohesive/non-cohesive materials using the discrete element method (DEM) has opened up as a new field of research in particulate technology. Fan et.al [1] have proved that the DEM can be successfully adopted to simulate particle mixing. This paper concentrates on the interdisciplinary research work that combines concrete technology, nanotechnology, and particulate technology to achieve uniform dispersion of nano-silica (NS) in cement that forms a binary mixture. The nanopowder acts as the active ingredient and the cement acts as the medium of dispersion.

In this research work, DEM-based software EDEM was used to simulate the dry mixing of NS with cement in a Conical Mixer and a Mortar Mixer. The main objective of this simulation is to study the impact of the type of mixer on content uniformity. To be more specific, the influence of mixing patterns, dead zones, and the blade of the mixer on achieving content uniformity is studied. Segregation Index (SI) is used to determine content uniformity. SI is a function of time and ratio of particle number in a binary particulate system for different particle sizes [13].

The content uniformity depends on many factors such as transferring of the material into the mixer, the actual mixing, discharge of the mix from the mixer, transportation of the materials, storage of the mix, etc. along with the type of the mixer. The various stages of mixing the two types of mixers are depicted in figures 1 and 2. The interaction-less area between the circumference of the bottom of the mixer and blade is known as dead zone and similar zones were observed at many places in the mixer depending on the type of the mixer by Krenzer et al. [2,3] in the study of the behavior of wet mixing of concrete in the Mortar Mixer. Due to the presence of such zones, the uniformity of the mix and degree of mixing is poor as shown in Fig. 2 (c).

                                                                                                                                                                                                

Unlike mortar mixers, the efficiency of mixing is mainly attributed to the influence of helical shaped screw in the Conical Mixer which results in the repeated cyclic flow pattern and three-dimensional particle flow in the mixer. As a result, there are no dead zones in the Conical Mixer. The type of mixer plays a predominant role and thus optimization of the mixing process in achieving content uniformity.

How to Cite

Meda, U. S., B, B., & Radhakrishna. (2021). Influence of mixers on dry dispersion of nanoparticles in the cementitious composites. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/319
Abstract 10 |

Article Details

Keywords

Content Uniformity, Mixing Quality, Dry dispersion of nanomatetials, Discrete Element Method, Simulation of particulate mixing

References
[1] H. Fan, D. Guo, J. Dong, X. Cui, M. Zhang, Z. Zhang, Discrete element method simulation of the mixing process of particles with and without cohesive interparticle forces in a fluidized bed, Powder Technol., 327, 223–231 (2018). https://doi.org/10.1016/j.powtec.2017.12.016.
[2] G. R Chandratilleke, G. R., Yu, A. B., Bridgwater, J., & Shinohara, K., A particle-scale index in the quantification of mixing of particles, AIChE J. 58, 1099–1118 (2011). https://doi.org/10.1002/aic.12654.
[3] K. Krenzer, V. Mechtcherine, U. Palzer, simulating mixing processes of fresh concrete using the discrete element method (DEM) under consideration of water addition and changes in moisture distribution, Cem. Concr. Res. 115 ,274–282 (2019). https://doi.org/10.1016/j.cemconres.2018.05.012.
[4] K. Krenzer, V. Mechtcherine, U. Palzer, simulating mixing processes with water addition using DEM - From bulk material to suspension, Proc. 4th Int. Conf. Part. Methods - Fundam. Appl. Part. 2015. 722–731(2015).
Section
GM1: Materials

Most read articles by the same author(s)

1 2 > >>